Stroke Risk Stratification through Plaque Motion Analysis of Longitudinal Carotid

通过颈动脉纵向斑块运动分析进行中风风险分层

• 批准号: 7926175
• 负责人: Eduardo Simon Barriga
• 金额: $ 19.99万
• 依托单位: VISIONQUEST BIOMEDICAL, LLC
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7926175
• 关键词: American Heart Association; Arterial Fatty Streak; Arteries; Atherosclerosis; Behavior; Blood Vessels; Blood flow; Businesses; Cardiac; Cardiovascular system; Carotid Arteries; Cessation of life; Characteristics; Classification; Clinical; Clinical Data; Collaborations; Computer Assisted; Data; Development; Devices; Diagnosis; Diagnostic; Early Diagnosis; Equipment; Evaluation; Frequencies; Goals; Grant; Image; Imagery; Intervention; Lead; Lipids; Maps; Measurement; Measures; Methodology; Methods; Metric; Monitor; Morphology; Motion; Nature; Obesity; Optics; Patients; Pattern; Populations at Risk; Procedures; Protocols documentation; Radial; Radio; Resolution; Risk; Risk Assessment; Rupture; Screening procedure; Signal Transduction; Specialist; Stenosis; Stratification; Stroke; Surface; System; Techniques; Testing; Transient Ischemic Attack; Ultrasonography; Vendor; World Health Organization; base; calcification; clinical practice; cost; imaging Segmentation; improved; innovation; interest; longitudinal analysis; method development; novel; public health relevance; tool; vector

DESCRIPTION (provided by applicant): The goal of this application is to develop optimal methods for estimating atherosclerotic plaque deformation through the cardiac cycle from ultrasound videos of the carotid artery. The proposed methodology will allow clinicians to visualize how different atherosclerotic plaque components deform throughout the cardiac cycle and to identify how these deformations correlate with stroke risk assessment. Our methodology will provide an innovative system for accurately stratifying risk of stroke from plaque deformations. As the preliminary results indicate, we will be able to discriminate between the large deformations of hypoechoic (dark), unstable plaque regions and the small deformations of hyperechoic (bright), stable plaque regions. By quantifying the deformations over the entire cardiac cycle, we will be able to monitor large changes in the behavior of the different plaque components. These results will advance our understanding of how plaque instability can lead to increased risk of stroke. The demonstration of this technique as part of computer-aided diagnostic system will have major commercial interest with vendors of ultrasound equipment and vascular specialists. The visualization of the instabilities associated with the hypoechoic plaque regions, which include lipid regions, will provide a clear, early indication of how obesity can lead to stroke. Early detection can directly contribute to reducing the current ratio that attributes 1 out of every 16 US deaths to stroke (World Health Organization). Last year, over 6 million cardiovascular-related deaths had atherosclerosis as the underlying cause (American Heart Association). The business opportunities are significant in the sense that this new, inexpensive, clinical methodology can be widely deployed as a standard screening tool for the at risk population. In collaboration with our clinical team, we will develop the clinical acquisition protocol for use with standard 2D ultrasound devices. The innovation in the proposed approach comes from the development of several new methods developed by the principal collaborators. This includes the development of methods for standarding the ultrasound image acquisition, plaque component estimation, m-mode estimation, image segmentation and robust motion and deformation estimation. The focus of our application is in the development of new methods for robust motion and deformation estimation. The basic idea is to use high values of cross-correlation to get coarse but reliable motion estimates and use these estimates to help tune our optical-flow, pixel-based estimates. This hierarchical approach brings the well-established robustness of the cross-correlation approach to the fine resolution, pixel based estimates of the optical flow methodology.

描述（由申请人提供）：本申请的目标是开发用于从颈动脉的超声视频估计心动周期中动脉粥样硬化斑块变形的最佳方法。所提出的方法将允许临床医生可视化不同的动脉粥样硬化斑块成分如何在整个心动周期中变形，并确定这些变形如何与中风风险评估相关。 我们的方法将提供一个创新的系统，准确分层斑块变形中风的风险。 初步结果表明，我们将能够区分低回声（暗），不稳定斑块区域的大变形和高回声（亮），稳定斑块区域的小变形。通过量化整个心动周期的变形，我们将能够监测不同斑块成分行为的大变化。 这些结果将促进我们对斑块不稳定性如何导致中风风险增加的理解。 作为计算机辅助诊断系统的一部分，这种技术的演示将对超声设备供应商和血管专家产生重大的商业利益。 与低回声斑块区域（包括脂质区域）相关的不稳定性的可视化将为肥胖如何导致中风提供明确的早期指示。早期发现可以直接有助于降低目前的比率，即每16例美国死亡中就有1例死于中风（世界卫生组织）。去年，超过600万心血管相关死亡的根本原因是动脉粥样硬化（美国心脏协会）。 这种新的、廉价的临床方法可以作为高危人群的标准筛查工具广泛部署，从这个意义上说，商业机会是重要的。我们将与我们的临床团队合作，开发用于标准2D超声设备的临床采集协议。 所提出的方法的创新来自于主要合作者开发的几种新方法的发展。这包括开发用于标准化超声图像采集、斑块成分估计、m模式估计、图像分割以及鲁棒运动和变形估计的方法。我们的应用程序的重点是在鲁棒的运动和变形估计的新方法的发展。其基本思想是使用高的互相关值来获得粗略但可靠的运动估计，并使用这些估计来帮助调整我们的光流，基于像素的估计。这种分层的方法带来了良好的稳健性的互相关方法的高分辨率，基于像素的估计的光流方法。